ORIGINAL RESEARCH ARTICLE
published: 23 September 2013
doi: 10.3389/fpsyg.2013.00614
The influence of high-level beliefs on self-regulatory
engagement: evidence from thermal pain stimulation
Margaret T. Lynn 1*, Pieter Van Dessel 2 and Marcel Brass 1,3
1
2
3
Department of Experimental Psychology, Ghent University, Gent, Belgium
Department of Experimental Clinical and Health Psychology, Ghent University, Gent, Belgium
Behavioral Science Institute, Radboud University, Nijmegen, Netherlands
Edited by:
T. Andrew Poehlman, Southern
Methodist University, USA
Reviewed by:
T. Andrew Poehlman, Southern
Methodist University, USA
Joaquin A. Anguera, University of
California San Francisco, USA
*Correspondence:
Margaret T. Lynn, Department of
Experimental Psychology, Ghent
University, Henri Dunantlaan 2,
B-9000 Ghent, Belgium
e-mail: [email protected]
Determinist beliefs have been shown to impact basic motor preparation, prosocial
behavior, performance monitoring, and voluntary inhibition, presumably by diminishing
the recruitment of cognitive resources for self-regulation. We sought to support and
extend previous findings by applying a belief manipulation to a novel inhibition paradigm
that requires participants to either execute or suppress a prepotent withdrawal reaction
from a strong aversive stimulus (thermal pain). Action and inhibition responses could
be determined by either external signals or voluntary choices. Our results suggest that
the reduction of free will beliefs corresponds with a reduction in effort investment that
influences voluntary action selection and inhibition, most directly indicated by increased
time required to initiate a withdrawal response internally (but not externally). It is likely that
disbelief in free will encourages participants to be more passive, to exhibit a reduction in
intentional engagement, and to be disinclined to adapt their behavior to contextual needs.
Keywords: free will, beliefs, inhibition, volition, effort, self-control, pain
INTRODUCTION
The question of whether free will truly exists is an age-old philosophical question, tackled by thinkers ranging from Democritus
to Russell. Yet most contemporary scientists have avoided the
metaphysical and existential hurdles of free will, and instead
investigate its impact on human action: how this phenomenon
arises in the mind, and to what extent deterministic beliefs have
an effect on our behavior (e.g., Wegner, 2003; Vohs and Schooler,
2008; Baumeister et al., 2009; Rigoni et al., 2011, 2012, 2013).
The sensation of control over one’s actions is an undeniably
ubiquitous feature of human experience. People tend to believe
they are responsible for a given action if the causal principles of
consistency, priority, and exclusivity are satisfied that is, if their
intentions are consistent with and experienced at a suitable interval prior to the relevant action, and there is no other reasonable
explanation for the action arising (Wegner, 2003). Perception
of personal control is further considered to be intrinsic, biologically necessary, and protective against environmental stressors
(Leotti et al., 2010).
Social psychological research has recently investigated the
degradation of behavioral and social effects thought to follow
from a belief in determinism. For instance, Vohs and Schooler
(2008) found that inducing disbelief in free will, via reading of
a determinist essay or series of statements, elicited an increase in
cheating on the part of participants. In comparison with control
subjects, anti-free will participants in this case paid themselves
a statistically improbable amount of money for performance on
a problem-solving task, and more frequently permitted themselves to view answers when given the opportunity to cheat.
Under similar conditions, Baumeister et al. (2009) found that
participants with weakened free will beliefs showed increased
aggression and decreased helping behavior. Likewise, an increase
www.frontiersin.org
in mindless conformity and a decrease in counterfactual thinking,
assumed to be adaptive for learning and social adaptation, have
been reported to accompany deterministic beliefs (Baumeister
et al., 2011; Alquist et al., 2013). Interestingly, when these studies
included a condition promoting free will, results were consistent
with the control group, suggesting that a belief in free will is a
common default state.
More recent research in the domain of Cognitive Psychology
has revealed an impact of deterministic beliefs even on basic
levels of motor control. Rigoni et al. (2011) used a manipulation identical to that of Vohs et al. (2008, Experiment 1) to alter
participants’ belief in free will. They observed that participants
who were induced to disbelief in free will showed reduced amplitudes of the readiness potential, an electrophysiological marker of
unconscious motor preparation (Rigoni et al., 2011). In a subsequent study (Rigoni et al., 2013) it was found that performance
monitoring, as indicated by post-error slowing, was also diminished in participants induced to disbelieve in free will. This may
indicate a reduction in the recruitment of self-regulatory processes, and less inclination to adjust one’s behavior according to
circumstantial needs, on the part of anti-free will participants.
Finally, this belief manipulation has been applied to an
important facet of self-control, namely intentional inhibition,
or the ability to voluntarily suppress a prepotent action plan
(Brass and Haggard, 2007). The study in question (Rigoni
et al., 2012) employed a task developed by Kühn et al. (2009)
that overcame a limitation of the well-supported literature on
externally-generated stopping (see Aron, 2007, for a review) by
enabling voluntary choice behavior to be experimentally investigated within an inhibition paradigm. In this task, participants
were occasionally asked to freely decide whether to stop a
prepared action (button pressing to halt the progress of a marble
September 2013 | Volume 4 | Article 614 | 1
Lynn et al.
rolling down a ramp). Both intentional inhibition and perceived
self-control were shown to be adversely affected by an anti-free
will manipulation (Rigoni et al., 2012). These findings were interpreted such that weakened free will beliefs lead to a reduction
in intentional effort, which then causes participants to select
the less demanding response option (in this case to execute the
pre-planned response).
The goal of the present study was to support and extend
prior research on the influence of free will beliefs upon intentional inhibition, by investigating whether inducing determinist
beliefs might in turn influence one’s intentional engagement in
self-regulatory behavior. However, while previous studies have
investigated intentional inhibition in rather artificial experimental situations in which participants have hardly any prior motivation to act or inhibit, we sought to address voluntary inhibition
in a more ecologically valid setting in which behavioral urges are
present. To this end, our secondary goal was to develop and pilot a
novel experimental paradigm for disentangling intentional from
instructed inhibition.
Pain was selected as the behaviorally relevant stimulus for our
purposes. Management of the pain avoidance response can be
seen as a compelling component of the affective response system;
the organism is strongly motivated to avoid the pain sensation
(Campbell and Misanin, 1969; Elliot, 2006). We can therefore
consider management of this urge as a window into how we suppress our most basic drives, and a classical instance of self-control.
The pain avoidance response can of course be highly automatized,
for instance when one reflexively jerks their hand away from a
hot stove. However, at times other goals call for self-control to be
exerted for the suppression of this avoidant urge, such as when
the heat comes not from the stove, but from a plate of food. In
this case, one might choose to suppress the highly prepotent reaction momentarily in favor of satisfying the opposing basic urge of
hunger (cf. Morsella, 2005).
Our paradigm required participants to occasionally inhibit a
prepotent withdrawal reaction from a heat source applied to their
inner wrists. In half the trials, participants were able to choose
whether to inhibit the withdrawal response or to immediately terminate the trial. The advantage of this manipulation is that it
requires strong (and consistent; the urge to withdraw does not
fade) self-control to withstand the thermal pain. In that sense,
it is in stark contrast to standard laboratory tasks involving selfregulation and agency. The design also ensures that acting and
inhibiting were equally distributed in the non-choice, or directed,
trials, thereby discouraging any response bias and ensuring a
comparable number of trial in each design cell. To manipulate
free will beliefs, we used a Velten procedure (Velten, 1968) similar to that used in previous experiments (Vohs and Schooler,
2008, Experiment 2; Baumeister et al., 2009), in which participants are required to read and reflect upon a series of statements
(see Supplementary Material for a complete list). Immediately
prior to each trial, participants were presented with a statement and asked to retain the statement in memory until the
end of the block. Statements were either neutral or meant to
induce anti-free will beliefs (between-subjects). These statements
were shown during the inter-trial interval in order to reduce
potential pain preparation and decision-making strategies. We
Frontiers in Psychology | Cognition
High-level beliefs and self-regulatory engagement
hypothesized that inducing disbelief in free will would lead participants to exhibit a reduction in intentional engagement, to lack
adaptive strategies, and to be disinclined to adapt their behavior
to contextual needs.
METHODS
PARTICIPANTS
Fifty-four Dutch-speaking undergraduate students enrolled in
the study; all gave written consent prior to participation. They
received either course credit or a payment of 10 euros for
their participation. All participants had normal or corrected-tonormal vision and reported no neurological deficits. The study
was conducted in accordance with the Declaration of Helsinki,
and the approval of Ghent University’s Ethical Committee was
obtained in advance. After determining participants’ individual
pain thresholds, those who did not report sufficient pain (i.e.,
their threshold surpassed 50◦ —beyond the safety limitations of
the stimulating equipment) were removed from the study. A total
of 48 participants (12 male, tested individually) completed the
entire experiment.
PROCEDURE
Threshold determination
Pain was induced via a thermode connected to a Medoc
PATHWAY device (MEDOC, Haifa, Israel), an apparatus
designed to induce thermal pain using cold or hot stimulation.
The threshold at which participants felt sufficient pain was determined by exposing each participant to 26 trials in which the
thermal sensation gradually increased over 5 s from 32◦ C to a
randomized destination temperature between 45 and 50◦ C (in
increments of 0.25◦ ), a slope comparable to the experimental trials. After each trial, the thermode returned instantly to baseline
temperature, and participants were asked to rate their perceived
pain on a scale from zero to eight, with zero being no pain and
eight being the worst possible pain. The destination temperature
employed in the main experiment was computed for each participant as the highest temperature at which they rated their pain
as a six. This method was revealed during piloting to yield more
accurate tolerance threshold measurements than merely requiring
participants to indicate the maximum heat they could withstand
when exposed to a steadily increasing temperature. Importantly,
participants were free to press a button at any point during the
threshold determination in order to terminate the trial.
Task and stimuli
Participants received painful heat stimulation during each trial,
applied via a thermode to alternating inner wrists. The images
of three geometric shapes (triangle, square, circle) were used as
cues to indicate the trial type. Depending on the cue, participants
were requested to either press the button as quickly as possible
(“directed action,” 25% of trials), inhibit this response and endure
the pain (“directed inhibition,” 25% of trials), or make a voluntary decision to either button press immediately or persist until
the end of the trial (“choice,” 50% of trials). In the latter case,
participants were requested to make their choices approximately
equal over the course of the experiment, but not to use any particular strategies or to decide in advance of the presentation of the
September 2013 | Volume 4 | Article 614 | 2
Lynn et al.
cue. In a practice block, absent pain stimulation, participants were
trained on the cues. A pilot study had revealed that participants
are typically around 200 ms slower to respond on choice action
trials than on directed action trials, reflecting the additional time
needed for the choice decision. Accordingly, to make stimulation
as identical as possible across action conditions, 200 ms of thermal stimulation was added to directed action trials, following the
button press.
Each trial was preceded by a statement (“neutral” or “antifree will,” see below) with a duration of 12 s. After a delay of
1 s, a fixation cross was presented and the temperature of the
thermode began to gradually increase from a baseline of 32◦ C
to the participant’s individually determined threshold. After 5 s,
one of the three task cues appeared in place of the fixation cross.
The temperature remained at threshold for the next 2 s, or until
the participant pressed the button to terminate both the pain
stimulation and the trial. Afterwards, prompts for ratings of the
perceived pain and “urge to terminate the trial by pressing the
button” (both on a scale of 0–8) remained on screen until participants responded. Participants were then cued to alternate the
arm placed atop the thermode. The arm not being stimulated was
used to button press (thereby providing a response time for action
trials) and was placed atop the opposing wrist, in order to lend
weight and make it more difficult for participants to inadvertently
withdraw from pain rather than button pressing. A schematic
overview of a possible trial in the anti-free will condition is
presented in Figure 1.
The assignment of geometric shapes to trial types, and the
order of the first-stimulated wrist were counterbalanced across
subjects. Each participant had to perform 120 trials in total,
High-level beliefs and self-regulatory engagement
being divided into six blocks of 20 trials presented in randomized
sequence. In each block, participants were given 10 trials in which
they were cued to make a decision, five trials in which they were
cued to push and five trials in which they were cued to inhibit
their withdrawal response. Importantly, participants were free to
press a button to immediately terminate the thermal sensation at
any point during the experiment.
Manipulation of free will beliefs
Participants were randomly assigned to either the control condition or the anti-free will condition (24 in each condition). All
participants were required to read discrete statements presented
on-screen during the inter-trial interval. They were instructed to
retain this information until the end of the block, at which point
a probe question concerning statement recognition was presented
on the screen (see Supplementary Material). The probe questions
were inserted to verify that participants had attended to the statements as directed, and to support a cover story that the study’s
goal was to test the influence of pain on memory. After feedback
on the accuracy of their answer was given, a novel set of statements was presented, and subjects were instructed to remember
these subsequent statements instead. The statements were either
neutral or designed to tap into free will beliefs, with 60 unique
statements in each group. Over the course of the experiment,
control participants were exposed to each of the 60 neutral statements twice, while participants in the anti-free will condition
were shown each of the 60 statements related to free will beliefs
twice. Furthermore, in the anti-free will condition, the three trial
types (directed action, directed inhibition, choice) were divided
equally over each of the three statement categories.
FIGURE 1 | Schematic overview of a sample block (Anti-free will condition). Note that there was no time limit for pain and urge rating responses.
www.frontiersin.org
September 2013 | Volume 4 | Article 614 | 3
Lynn et al.
A total of 90 statements were collected from a variety of questionnaires and articles involving free will beliefs (e.g., Carey, 2005;
Vohs and Schooler, 2008; Paulhus and Carey, 2011), or were
produced based on these inventories. These 90 statements were
selected with the aim of being related to certain aspects of free
will beliefs; 30 statements were related to the idea that people
do not have a free will (e.g., “scientists tell us that people have
no free will”), thirty statements concerned beliefs in scientific
determinism (e.g., “the environment someone is raised in determines their success as an adult”) and 30 statements were related
to beliefs in fatalistic determinism (e.g., “you can’t change your
destiny, no matter how hard you try”). Another 90 neutral statements were selected, stating facts and ideas that were unrelated
to beliefs in free will (e.g., “an ostrich’s eye is bigger than its
brain”).
The combined 180 statements were then rated online (http://
www.thesistools.com) by 38 participants, none of whom participated in the main experiment. Participants rated how difficult
they would find the statement to recall, and the degree to which
the statement was in line with either a disbelief in free will, a
belief in scientific determinism, or a belief in fatalistic determinism. These questions were based on the factors laid out by Paulhus
and Carey (2011) and were expressed in layman’s terms for ease
of understanding.
A total of 120 statements were selected based on the ratings
drawn from this pre-test. The 20 statements that had received
the highest ratings in each belief category were chosen, for a
total of 60 experimental statements. Sixty neutral statements were
matched for difficulty with these statements. Crucially, the experimental statements and the control statements did not differ
with regard to their difficulty to recall (experimental: M = 1.59;
neutral: M = 1.60), t(7) = 0.86, p = 0.82.
Questionnaires
Two days prior to their participation in this study, participants
completed an array of questionnaires concerning memory, anxiety, and free will beliefs. Questions about memory and anxiety were inserted to support the aforementioned cover story.
Questions regarding free will beliefs consisted of the entire battery of the Free Will and Determinism questionnaire (FAD-Plus,
Paulhus and Carey, 2011). Following the experimental session,
participants were requested to complete the FAD-Plus questionnaire a second time to determine whether or not the experimental
statements had an effect on the relevant belief system.
High-level beliefs and self-regulatory engagement
Condition, F(1, 46) = 4.19; p < 0.05 (Figure 2), such that participants in the experimental condition scored significantly higher
after the experiment than before (Post-test: M = 80.0, SD = 8.9;
Pre-test: M = 76.3, SD = 8.5), t(23) = 3.23, p < 0.01, indicating
a weakening of beliefs in free will. No such effect was observed
for participants in the control condition (Post-test: M = 76.9,
SD = 8.9; Pre-test: M = 76.6, SD = 9.4), t(23) = 0.29, p = 0.78.
DATA PREPARATION
Despite efforts toward optimizing the pain threshold procedure,
the grand mean pain rating across participants was rather low
(M = 4.6; SD = 1.11). Crucially, in the debriefing questionnaire,
more than half (N = 26) of all participants stated that they had
not needed to exert any effort to withhold the pain-withdrawal
response during the experiment. As pain is a key factor in this
experiment, we decided to restrict our analyses to participants
that reported a sufficient level of pain throughout the whole of
the experiment. We therefore excluded all participants with mean
pain ratings lower than the median of the subjective pain scale,
namely 4.5. All further analyses were performed on this subset of
25 “high pain” participants (8 male): 12 participants in the antifree will condition and 13 participants in the control condition.
Results for the excluded “low pain” participants may be found in
Supplementary Material.
BEHAVIORAL ANALYSES
Between-group means and standard deviations are reported in
Table 1.
Reaction times
On trials in which participants were cued to button press,
participants performed the correct response in nearly all trials (M = 99%, SD = 2%). We expected anti-free will participants to be significantly slower than controls, particularly on
choice trials. A mixed design ANOVA on RTs, with Instruction
RESULTS
MANIPULATION CHECK
To test the effectiveness of the belief manipulation, a mixed design
ANOVA was conducted on participants’ total FAD-scores before
and after the experiment using Time (Pre-test vs. Post-test) as
a within-subject factor and Belief condition (Anti-free will vs.
Control) as a between-subjects factor. Total FAD-scores were
calculated for each participant such that higher values indicate
less belief in free will, by reverse scoring the Free Will subscale and combining it with the other three subscales (Scientific
Determinism, Fatalistic Determinism, and Unpredictability). The
analysis revealed a significant interaction between Time and Belief
Frontiers in Psychology | Cognition
FIGURE 2 | Mean total scores on the FAD-Plus questionnaire as a
function of Belief condition (Control vs. Anti-free will) and Time
(Pre-test vs. Post-test). Higher scores indicate increased disbelief in
free will.
September 2013 | Volume 4 | Article 614 | 4
Lynn et al.
High-level beliefs and self-regulatory engagement
(Choice vs. Directed) as a within-subjects factor and Belief condition (Anti-free will vs. Control) as a between-subjects factor,
revealed a main effect of Instruction, F(1, 23) = 79.310, p < 0.01,
such that participants were slower to respond on choice trials (Choice: M = 807 ms, SD = 158 ms; Directed: M = 567 ms,
SD = 108 ms), consistent with piloting and reflecting the time
needed for a response decision. A main effect of Belief condition revealed a non-significant trend, F(1, 23) = 2.958, p =
0.099, indicating that anti-free will participants tended to be
slower to respond than controls (though this interpretation
should be approached with caution due to the marginal significance level). Further, the interaction between Instruction
and Belief condition trended toward significance, F(1, 23) =
2.928, p = 0.10. Planned comparisons revealed an RT difference
between anti-free will participants and controls on choice action
trials, t(23) = −2.07, p < 0.05, Cohen’s d = 0.84 (Figure 3),
such that anti-free will participants were significantly slower to
respond when given a choice than were controls. No such effect
was found on directed action trials, t(23) = −0.69, p = 0.497,
d = 0.27.
Table 1 | Between-group means and standard deviations.
Control
Anti-free will
Correlation of FAD difference scores with choice reaction times
To examine the relationship between participants’ RTs and free
will beliefs more thoroughly, we performed an additional correlation analysis. The aim of this analysis was to test to what extent
the slowed responding on choice action trials was related to the
effectiveness of the belief manipulation. To this end, we first computed each participant’s change in anti-free will beliefs, across
experimental condition (control participants were included to
ensure sufficient variability), by subtracting participants’ postexperimental scores on the anti-free will subscale of the FAD
from their pre-experimental scores. Second, we computed a difference score of participants’ mean RTs on choice and directed
action trials to create an index of each participant’s decision time
at pushing the button. There was a significant positive correlation between the two difference scores, r(23) = 0.40, p < 0.05
(Figure 4), reflecting that those subjects who showed a stronger
reduction in free will beliefs were also slower to make the decision
to press the button.
Proportion of inhibition on choice trials
On trials in which participants were cued to choose between acting and inhibiting, participants opted to inhibit in 41.47% of all
trials (SD = 9.76%). The proportion of inhibition on choice trials was analyzed in an independent-samples t-test, revealing no
significant difference between anti-free will participants and controls, t(23) = −0.462, p = 0.648. This lack of a difference between
experimental groups, which is in contrast to the findings of Rigoni
et al. (2012), may be due to the experimental design, which, unlike
previous studies, discourages response biases by using an equal
proportion of directed action and inhibition trials.
Mean
SD
Mean
SD
All action trials
658
124
736
101
Choice action trials
748
162
871
133
Directed action trials
552
121
582
94
RATINGS
Proportion inhibition (%)
40.59
9.64
42.43
10.22
Pain ratings
Pain ratings (across trials)
5.5
0.9
5.4
0.6
We began by computing pain ratings across all participants for
the first and second halves of the experiment to ensure that
Reaction times (ms)
URGE ratings
Across trials
4.4
1.3
4.7
1.5
Choice trials
4.5
0.4
4.5
0.4
Directed trials
4.3
0.4
4.8
0.3
FIGURE 3 | Reaction times on press trials, between-subjects. Note:
values depicted are means and standard errors.
www.frontiersin.org
FIGURE 4 | Correlation of difference scores (post-test minus pre-test)
on the anti-free will subscale of the FAD-Plus with the decision
response time index (mean response times on choice minus directed
trials).
September 2013 | Volume 4 | Article 614 | 5
Lynn et al.
participants did not adapt to the pain stimulation over the course
of the experiment. No differences in pain ratings were observed
between the trials of the first and the second half of the experiment (First half: M = 5.4, SD = 0.8; Second half: M = 5.5, SD =
0.8), t(24) = −0.58, p = 0.57.
Participants reported a grand mean pain rating of 5.5 (SD =
0.74). Pain ratings were analyzed in a mixed design ANOVA
using Belief condition as a between-subjects factor, and Response
(Action vs. Inhibition) and Instruction (Directed vs. Choice)
as within-subject factors. The main effect of Belief condition
was not significant, F(1, 23) = 0.13, p = 0.73, reflecting that subjective pain across trials was equivalent for the two groups.
However, there was a significant main effect of Response (Action:
M = 5.3, SD = 0.2; Inhibition: M = 5.7, SD = 0.1), F(1, 23) =
12.60, p < 0.01, indicating higher perceived pain on inhibition
compared with action trials, presumably due to the lengthier
pain stimulation. Moreover, there was an interaction effect of
Response × Instruction, F(1, 23) = 7.94, p = 0.01, reflecting that
inhibition trials were rated as less painful when they were voluntarily chosen rather than instructed (Choice: M = 5.5, SD = 0.8;
Directed: M = 5.8, SD = 0.6), t(24) = 3.38, p < 0.01, while there
was no such difference between chosen and directed action trials (Choice: M = 5.4, SD = 1.0; Directed: M = 5.2, SD = 0.9),
t(24) = −1.54, p = 0.14. Importantly, the lack of a difference
between the mean pain ratings of anti-free will and control participants suggests that our findings are not solely due to differences
in the overall subjective experience of pain.
Urge ratings
Participants reported a grand mean urge rating of 4.5 (SD = 1.4).
Urge ratings were analyzed with a mixed design ANOVA akin
to that of the pain ratings. The analysis revealed a significant
main effect of response, reflecting greater urges on action trials (Action: M = 4.8, SD = 0.3; Inhibition: M = 4.2, SD = 0.3),
F(1, 23) = 4.98, p < 0.05. There was also a significant interaction effect of Response × Instruction, F(1, 23) = 6.49, p < 0.05.
Consistent with the pain ratings, participants reported a reduced
urge on choice compared with directed inhibition trials (Choice:
M = 4.0, SD = 1.6; Directed: M = 4.5, SD = 1.7), t(24) = 2.67,
p < 0.05, while there was no such difference between choice and
directed action trials (Choice: M = 5.0, SD = 1.4; Directed: M =
4.6, SD = 1.6), t(24) = −1.70, p = 0.10. The main effect of Belief
condition was not significant, F(1, 23) = 0.10, p = 0.76. Crucially
however, there was a significant interaction effect of Belief condition × Instruction, F(1, 23) = 6.22, p < 0.05. Post-hoc t-tests
revealed that participants in the anti-free will condition tended
to report a stronger urge to press on directed trials than on choice
trials, t(11) = 2.044, p = 0.066, whereas this was not the case for
control subjects, t(12) = −1.465, p = 0.17 (Figure 5). This may
be indicative of a greater urge to act when externally instructed
on the part of anti-free will participants. Similar results were
obtained by Alquist et al. (2013), who found that anti-free will
participants conformed more to external pressure.
ADAPTIVE STRATEGIES ON CHOICE TRIALS
Based on the hypothesis that anti-free will participants might lack
adaptive strategies, we conducted an exploratory analysis in which
Frontiers in Psychology | Cognition
High-level beliefs and self-regulatory engagement
FIGURE 5 | Urge ratings as a function of Instruction (Choice vs.
Directed) and Belief condition (Control vs. Anti-free will). Note: values
depicted are means and standard errors.
we investigated whether preceding trial pain or trial type had an
influence on response selection during choice trials. We assumed
that high pain trials might create a strong incentive to “quit” when
subsequently given a choice, thereby activating a strategy that is
protective of the organism. Similarly, participants might attempt
to create subjectively easier response sequences when granted the
opportunity. These strategies would presumably only be present
for control participants, as anti-free will participants tend to be
less inclined to adjust their behavior to the present situation
(Rigoni et al., 2013).
Pain on preceding trial
To investigate the influence of pain on subsequent choice behavior, we computed each participant’s mean pain rating for the trials
preceding choice inhibition and choice action trials. A mixed
design ANOVA with factors of Belief condition (Anti-free will vs.
Control) and Response (Choice Action vs. Choice Inhibition) was
then conducted on mean pain rating for n-1 trials. The analysis
revealed no main effects or interactions, Fs < 0.838, ps > 0.36,
indicating that pain ratings on the preceding trial did not differ between choice inhibition and choice action trials, for either
experimental group. This would suggest that participants do not
use recent pain as a factor in deciding whether to act or inhibit
when given the choice.
Response styles
To investigate response styles, we computed mean proportions
of inhibition during choice trials following each of the four trial
types. A mixed design ANOVA with factors of Belief condition
(Anti-free will vs. Control), n-1 Instruction (Choice vs. Directed),
and n-1 Response (Action vs. Inhibition) was then conducted
on mean proportion of inhibition in choice trials. This gave an
index of how often participants chose to inhibit rather than act
following a particular trial type (Figure 6). The analysis revealed
September 2013 | Volume 4 | Article 614 | 6
Lynn et al.
FIGURE 6 | N-1 trial contribution to response tendencies in each
experimental group. Compared with anti-free will participants (AFW),
control participants (CTRL) tend to inhibit less often following a directed
press trial. The dashed line indicates the grand mean proportion of
inhibition. ∗ p < 0.05.
a main effect of n-1 Instruction (Choice: M = 45.0% inhibition on subsequent choice trial; Directed: M = 38.7% inhibition
on subsequent choice trial), F(1, 23) = 6.366, p < 0.05, such that
participants tended to choose to inhibit more often following
a choice trial. There was also a significant interaction between
n-1 Instruction and n-1 Response, F(1, 23) = 11.460, p < 0.01,
such that participants chose to inhibit more often following a
choice action trial (M = 52.2%) than any other trial type (Choice
Inhibit n-1 = 37.9%; Directed Action n-1 = 35.5%; Directed
Inhibition n-1 = 41.7%), ts > 2.64, ps < 0.05. Furthermore,
there was a non-significant trend toward an interaction between
n-1 Response and Belief condition, F(1, 23) = 3.523, p = 0.07.
Anti-free will participants tended to inhibit more often following an action trial (M = 48.0%) than an inhibition trial (M =
38.6%), t(11) = −2.164, p = 0.05, d = 0.63, whereas this was not
the case for controls (Action n-1: M = 40.0%; Inhibition n-1:
M = 40.8%), t(12) = 0.251, p = 0.806, d = 0.03. This may indicate a more explicit tendency to alternate in an attempt to satisfy
the 50% choice instruction. Finally, post-hoc t-tests confirmed
that the primary difference in proportion of inhibition between
experimental groups lay in directed action n-1 trials. Control
subjects chose to inhibit significantly less often than anti-free
will participants following a directed action trial (Control: M =
29.7%; Anti-free will: M = 41.7%), t(23) = −2.490, p < 0.05,
d = 0.99. This may be indicative of an additional adaptive strategy on the part of control participants, as response repetitions are
subjectively less effortful than response switches.
DISCUSSION
In the present study, we employed a novel experimental approach
using thermal pain stimulation in order to demonstrate the
moderating nature of high-level beliefs on self-regulation. In particular, we sought to probe whether reducing participants’ belief
in free will could lead to a form of intentional disengagement
www.frontiersin.org
High-level beliefs and self-regulatory engagement
that influences selection and inhibition of action within a “hot”
motivational system (Metcalfe and Mischel, 1999).
In line with our predictions, participants who were induced
to disbelieve in free will were significantly slower to initiate a
response on trials in which they chose to act in order to terminate
the pain stimulation. This directly corresponds to the hypothesis that anti-free will participants would exhibit less intentional
engagement. Interestingly, this effect is only evident when a pain
avoidance response has to be executed internally rather than
externally, suggesting not a global passivity, but rather a specific
impairment in intentional self-regulation. This dissociation is in
accordance with previous evidence that intentional and stimulusdriven actions rely on distinct functional (Herwig et al., 2007) and
neural (Müller et al., 2007) mechanisms. The amount of slowing on choice action trials was furthermore correlated with the
degree of the effectiveness of the belief manipulation, suggesting
a direct link between the weakening of free will beliefs and the
voluntary management of a behavioral response to an aversive
stimulus. This mirrors the finding by Rigoni et al. (2011) in which
decreases in the readiness potential were correlated with a change
in anti-free will scores.
Moreover, anti-free will participants reported greater urges
to terminate the trial when their behavior was guided by the
cue compared to when they were able to freely choose, suggesting a disengagement from the task when externally instructed.
Importantly, and in contrast with previous studies (e.g., Kühn
et al., 2009; Rigoni et al., 2012), the aforementioned differences
are not confounded by differential response biases, as the proportion of inhibition in choice trials was equivalent between control
and anti-free will participants.
Our analysis of potentially adaptive strategies revealed surprising results. Participants do not appear to use recent pain as a
criterion in deciding whether to act or inhibit when given the
choice. However, we do find differences between the experimental groups in terms of their response styles. Interpretations are
merely speculative at this point, but it seems plausible that this
effect could be related to minimizing cognitive effort (e.g., Kool
et al., 2010). For instance, one could suppose that control participants select a subjectively easier strategy when exhibiting a bias
to repeat an action response (e.g., Mayr and Bell, 2006). On the
other hand, one could interpret the anti-free will participants as
selecting the less effortful strategy, by avoiding two (subjectively
more painful) inhibition trials in a row (e.g., law of least effort,
Hull, 1943). In the future, this could be disentangled by presenting blocks composed solely of choice trials in order to determine,
via longer choice trial sequences, which is the favored strategy:
response repetitions or avoidance of effortful combinations.
Taken together, the present study supports and extends previous research on intentional inhibition (Brass and Haggard, 2007;
Kühn et al., 2009; Filevich et al., 2012; Rigoni et al., 2012). In particular, it is the first to investigate voluntary inhibition of behavior in an ecologically valid experimental setting that involves
hot motivational systems rather than entirely arbitrary choices.
Participants reported less pain and a reduced urge to terminate
the trial on choice inhibition trials compared with directed inhibition trials, while choice and directed press trials were more
comparable. Thus, the pain paradigm we introduce offers an
September 2013 | Volume 4 | Article 614 | 7
Lynn et al.
High-level beliefs and self-regulatory engagement
effective way to dissociate between voluntary and instructed inhibition on a behavioral level, which opens the door to new ways
of investigating inhibition in which behaviorally-relevant options
are available to the participant.
That being said, as this study served as a first pilot of a
novel paradigm, our investigation must be seen as exploratory in
nature, and our conclusions considered accordingly. The exclusion of participants who did not experience sufficient pain levels is an unfortunate limitation of the present line of research
(Supplementary Material includes a summary of the excluded
participants’ results, for a comprehensive overview of our findings). Future studies should endeavor to ensure that a sufficient
pain tolerance threshold is obtained for each participant, or that
unsuitable participants are excluded in advance of testing. This
may require rigorous pre-testing of criteria such as whether participants are able to reliably report their tolerance thresholds, and
whether or not they adapt too quickly to pain over the course of
the experiment.
On a larger scale, the observed effects also exemplify a growing body of research that reveals the influence of higher-order
beliefs and metacognitions on behavioral control. As discussed
earlier, determinist beliefs have been shown to have an effect on
prosocial behavior (Vohs and Schooler, 2008; Baumeister et al.,
2009, 2011), basic motor and cognitive processes (Rigoni et al.,
2011, 2013), intentional inhibition (Rigoni et al., 2012), and now
on self-regulation of a “hot” incentive response system (Morsella,
2005). Yet free will beliefs are not the only higher-order cognitions capable of influencing a variety of processes underlying
behavioral control.
For instance, one factor that has been proposed to have a
strong influence on self-control is “ego depletion,” or the phenomenon in which exertion of self-control exhausts a common
regulatory resource, leading to hindered performance on subsequent tasks (Muraven et al., 1998; Vohs et al., 2008; Baumeister
et al., 2009; Hagger et al., 2010). However, recent research
has revealed that participants’ relevant belief systems are likely
to be more crucial than actual depletion when it comes to
REFERENCES
Alquist, J., Ainsworth, S., and
Baumeister, R. (2013). Determined
to conform: disbelief in free will
increases conformity. J. Exp. Soc.
Psychol. 49, 80–86. doi: 10.1016/j.
jesp.2012.08.015
Aron, A. (2007). The neural basis
of inhibition in cognitive control. Neuroscientist 13, 214–228. doi:
10.1177/1073858407299288
Baumeister, R. F., Crescioni, A. W., and
Alquist, J. L. (2011). Free will as
advanced action control for human
social life and culture. Neuroethics
4, 1–11. doi: 10.1007/s12152-0109058-4
Baumeister, R. F., Masicampo, E. J., and
DeWall, C. N. (2009). Pro-social
benefits of feeling free: manipulating disbelief in free will increases
aggression and reduces helpfulness.
Frontiers in Psychology | Cognition
Pers. Soc. Psychol. Bull. 35, 260–268.
doi: 10.1177/0146167208327217
Brass, M., and Haggard, P. (2007).
To do or not to do: the neural signature of self-control.
J. Neurosci. 27, 9141–9145. doi:
10.1523/JNEUROSCI.0924-07.2007
Campbell, B. A., and Misanin, J. R.
(1969). Basic drives. Annu. Rev.
Psychol. 20, 57–84. doi: 10.1146/
annurev.ps.20.020169.000421
Carey, J. M. (2005). Development and
Validation of a Measure of Free
will Belief and its Alternatives
(Unpublished
manuscript).
Vancouver: The University of
British Columbia.
Clarkson, J. J., Hirt, E. R., Jia, L.,
and Alexander, M. B. (2010).
When perception is more than
reality: the effects of perceived
versus actual resource depletion on
self-regulatory capacity. For instance, Job et al. (2010) demonstrated that only participants who thought of willpower as a
limited resource demonstrated the typical pattern of ego depletion, while the effect was completely absent in participants who
lacked this conviction. Similarly, Clarkson et al. (2010) found that
regardless of how depleted participants actually were, if they perceived themselves as less depleted, they failed to demonstrate ego
depletion effects during subsequent task performance (see also
Vohs et al., 2012).
These observations indicate that beliefs regarding regulatory resources are distinct from the resources themselves, and
can impact task performance independently. The present study
complements this line of research. There is little incentive for
engagement in self-control under the assumption that behavior is fully determined, and in this way free will beliefs are able
to influence the decision to exert regulatory effort. Accordingly,
assumptions about the existence of free will can be considered as
operating in parallel with beliefs about regulatory capacities. The
former speaks to one’s motivation to engage in self-regulation,
while the latter informs one’s available resources for self-control.
Moreover, while the aforementioned ego depletion studies have
examined task-relevant beliefs as stable traits, here we demonstrate the relevance of lay beliefs more directly by manipulating
them experimentally. Our findings therefore indicate that the
impact of higher-order beliefs on self-regulatory engagement is
not limited to stable, trait-like effects, but that even subtle statelike fluctuations in the strength of beliefs can affect the amount
of effort that people invest in self-control. A fundamental belief
in control over one’s actions may therefore prove to be an integral
prerequisite for self-regulatory investments. Future studies should
more directly investigate the mechanisms by which higher-order
beliefs impact the recruitment of self-control.
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: http://www.frontiersin.org/Cognition/10.3389/fpsyg.
2013.00614/abstract
self-regulatory behavior. J. Pers. Soc.
Psychol. 98, 29–46. doi: 10.1037/
a0017539
Elliot, A. (2006). The hierarchical
model of approach-avoidance
motivation. Motiv. Emot. 30,
111–116. doi: 10.1007/s11031-0069028-7
Filevich, E., Kühn, S., and Haggard,
P. (2012). Intentional inhibition
in human action: the power of
‘no.’ Neurosci. Biobehav. Rev.
36, 1107–1118. doi: 10.1016/j.
neubiorev.2012.01.006
Hagger, M. S., Wood, C., Stiff, C., and
Chatzisarantis, N. L. D. (2010). Ego
depletion and the strength model
of self-control: a meta-analysis.
Psychol. Bull. 136, 495–525. doi:
10.1037/a0019486
Herwig, A., Prinz, W., and Waszak,
F. (2007). Two modes of
sensorimotor
integration
in
intention- based and stimulusbased actions. Q. J. Exp. Psychol. 60,
1540–1554. doi: 10.1080/17470210
601119134
Hull, C. L. (1943). Principles
of Behavior. New York, NY:
Appleton-Century.
Job, V., Dweck, C. S., and Walton, G. M.
(2010). Ego depletion—is it all in
your head. Implicit theories about
willpower affect self-regulation.
Psychol. Sci. 21, 1686–1693. doi:
10.1177/0956797610384745
Kool, W., McGuire, J. T., Rosen, Z.
B., and Botvinick, M. M. (2010).
Decision making and the avoidance of cognitive demand. J. Exp.
Psychol. Gen. 139, 665–682. doi:
10.1037/a0020198
Kühn, S., Haggard, P., and Brass, M.
(2009). Intentional inhibition: how
September 2013 | Volume 4 | Article 614 | 8
Lynn et al.
the “veto-area” exerts control. Hum.
Brain Mapp. 30, 2834–2843. doi:
10.1002/hbm.20711
Leotti, L. A., Iyengar, S. S., and
Ochsner, K. N. (2010). Born to
choose: the origins and value
of the need for control. Trends
Cogn. Sci. 14, 457–463. doi:
10.1016/j.tics.2010.08.001
Mayr, U., and Bell, T. (2006). On
how to be unpredictable: evidence
from the voluntary task-switching
paradigm. Psychol. Sci. 17, 774–780.
doi:
10.1111/j.1467-9280.2006.
01781.x
Metcalfe, J., and Mischel, W. (1999).
A hot/cool-system analysis of
delay of gratification: dynamics of
willpower. Psychol. Rev. 106, 3–19.
doi: 10.1037/0033-295X.106.1.3
Morsella, E. (2005). The function
of phenomenal states: supramodular interaction theory. Psychol. Rev.
112, 1000–1021. doi: 10.1037/0033295X.112.4.1000
Müller, V., Brass, M., Waszak, F., and
Prinz, W. (2007). The role of the
preSMA and the rostral cingulate zone in internally selected
actions. Neuroimage 37, 1354–1361.
doi:
10.1016/j.neuroimage.2007.
06.018
www.frontiersin.org
High-level beliefs and self-regulatory engagement
Muraven, M., Tice, D. M., and
Baumeister, R. F. (1998). Selfcontrol as limited resource:
regulatory depletion patterns.
J. Pers. Soc. Psychol. 74, 774–789.
doi: 10.1037/0022-3514.74.3.774
Paulhus, D. L., and Carey, J. M. (2011).
The FAD-Plus: measuring lay beliefs
regarding freewill and related constructs. J. Pers. Assess. 93, 96–104.
doi: 10.1080/00223891.2010.528483
Rigoni, D., Kühn, S., Gaudino,
G., Sartori, G., and Brass, M.
(2012).
Reducing
self-control
by weakening belief in free will.
Conscious. Cogn. 21, 1482–1490.
doi: 10.1016/j.concog.2012.04.004
Rigoni, D., Kühn, S., Sartori, G.,
and Brass, M. (2011). Inducing
disbelief in free will alters brain
correlates of preconscious motor
preparation: the brain minds
whether webelieve in free will or
not. Psychol. Sci. 22, 613–618. doi:
10.1177/0956797611405680
Rigoni, D., Wilquin, H., Brass, M.,
and Burle, B. (2013). When errors
do not matter: weakening belief
in intentional control impairs
cognitive reaction to errors.
Cognition 127, 264–269. doi:
10.1016/j.cognition.2013.01.009
Velten, E. (1968). A laboratory task
for the induction of mood states.
Behav. Res. Ther. 6, 607–617. doi:
10.1016/0005-7967(68)90028-4
Vohs, K. D., Baumeister, R. F.,
Schmeichel,
B.
J.,
Twenge,
J. M., Nelson, N. M., and
Tice, D. M. (2008). Making
choices
impairs
subsequent
self-control: a limited-resource
account of decision making,
self-regulation, and active initiative. J. Pers. Soc. Psychol. 94,
883–893. doi: 10.1037/0022-3514.
94.5.883
Vohs, K. D., Baumeister, R. F.,
and Schmeichel, B. J. (2012).
Motivation,
personal
beliefs,
and limited resources all contribute to self-control. J. Exp.
Soc. Psychol. 48, 943–947. doi:
10.1016/j.jesp.2012.03.002
Vohs, K. D., and Schooler, J. (2008).
The value of believing in free
will: encouraging a belief in determinism increases cheating. Psychol.
Sci. 19, 49–54. doi: 10.1111/j.14679280.2008.02045.x
Wegner, D. M. (2003). The mind’s best
trick: How we experience conscious
will. Trends Cogn. Sci. 7, 65–69. doi:
10.1016/S1364-6613(03)00002-0
Conflict of Interest Statement: The
authors declare that the research
was conducted in the absence of any
commercial or financial relationships
that could be construed as a potential
conflict of interest.
Received: 09 April 2013; accepted:
21 August 2013; published online: 23
September 2013.
Citation: Lynn MT, Van Dessel P
and Brass M (2013) The influence
of high-level beliefs on self-regulatory
engagement: evidence from thermal pain
stimulation. Front. Psychol. 4:614. doi:
10.3389/fpsyg.2013.00614
This article was submitted to Cognition,
a section of the journal Frontiers in
Psychology.
Copyright © 2013 Lynn, Van Dessel
and Brass. This is an open-access article distributed under the terms of the
Creative Commons Attribution License
(CC BY). The use, distribution or reproduction in other forums is permitted,
provided the original author(s) or licensor are credited and that the original
publication in this journal is cited, in
accordance with accepted academic practice. No use, distribution or reproduction
is permitted which does not comply with
these terms.
September 2013 | Volume 4 | Article 614 | 9